Distributionally Robust Chance-Constrained Transactive Energy Framework for Coupled Electrical and Gas Microgrids

Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Somayeh Asadi, Rashed Khanjani

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


In this article, the transactive energy as a sustainable technology is introduced for the integration of numerous distributed energy resources (DERs) in a reliable manner. DERs can actively participate in the day-ahead (DA), real-time balancing (RTB), and wholesale gas markets for achieving the various goals. This article proposes a distributionally robust chance-constrained (DRCC) model based on the transactive energy approach for the optimal scheduling of microgrids in coupled electrical and gas networks. Optimal scheduling of DERs has been carried out for maximizing the microgrids' profits in the DA electricity and gas markets while minimizing the imbalance costs is an objective for microgrids in the RTB market. Transactive energy technology is used for managing energy exchange between microgrids and the power grid. Moreover, the linearization techniques are employed for avoiding nonlinear equations to obtain reliable results in a short time. Due to the effects of the electrical and gas networks on each other, the interactions between them are considered by investigating both the electrical and gas energy conversions in the real system. Simulation results are extracted considering two cases: Case I without DRCC and Case II with DRCC. Given the results, the cost of interrupted load, DERs, and gas sector in Case II are, respectively, reduced to 35.4%, 25.02%, and 17.1% in comparison with Case I. Moreover, the DRCC method guarantees the achievement of $169027.759 profit for microgrids, which is reduced to 47.85% in comparison with the base case.

Original languageEnglish (US)
Article number8960646
Pages (from-to)347-357
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Issue number1
StatePublished - Jan 2021

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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